Detecting spatial clusters of human scabies in Tigray, Ethiopia from 2018 to 2023.

Background: Scabies is one of public health concerns among communicable disease in Ethiopia, especially among disadvantaged and the poor. This current study aims to detect the spatiotemporal patterns of scabies in Tigray from 2018 to 2023 using scabies data aggregated at the zonal level. The study also examined the persistent patterns in the spatial variation of scabies incidence across the administrative regions during the study period.

Spatial disparities of HIV prevalence in South Africa. Do sociodemographic, behavioral, and biological factors explain this spatial variability?

Background: In 2021, an estimated 38 million people were living with human immunodeficiency virus (HIV) globally, with over two-thirds living in African regions. In South Africa, ~20% of South African adults are living with HIV. Accurate estimation of the risk factors and spatial patterns of HIV risk using individual-level data from a nationally representative sample is invaluable for designing geographically targeted intervention and control programs.

Spatial distribution and sociodemographic risk factors of malaria in Nigerian children less than 5 years old.

Malaria remains a leading cause of morbidity and mortality among children in Nigeria less than 5 years old (under-5). This study utilized nationally representative secondary data extracted from the 2015 Nigeria Malaria Indicator Survey (NMIS) to investigate the spatial variability in malaria distribution in those under- 5 and to explore the influence of socioeconomic and demographic factors on malaria prevalence in this population group. To account for spatial correlation, a Spatially Generalized Linear Mixed Model (SGMM) was employed and predictive risk maps was developed using Kriging.

Using mixed effects logistic regression models for complex survey data on malaria rapid diagnostic test results.

Background: The effect of malaria in Nigeria is still worrisome and has remained a leading public health issue in the country. In 2016, Nigeria was the highest malaria burden country among the 15 countries in sub-Saharan Africa that accounted for the 80% global malaria cases. The purpose of this study is to utilize appropriate statistical models in identifying socio-economic, demographic and geographic risk factors that have influenced malaria transmission in Nigeria, based on malaria rapid diagnostic test survey results.